Continuous glucose monitoring in healthy adults—possible applications in health care, wellness, and sports
Introduction: Continuous glucose monitoring (CGM) systems were primarily developed for
patients with diabetes mellitus. However, these systems are increasingly being used by …
patients with diabetes mellitus. However, these systems are increasingly being used by …
Review of methods for detecting glycemic disorders
M Bergman, M Abdul-Ghani, RA DeFronzo… - Diabetes research and …, 2020 - Elsevier
Prediabetes (intermediate hyperglycemia) consists of two abnormalities, impaired fasting
glucose (IFG) and impaired glucose tolerance (IGT) detected by a standardized 75-gram …
glucose (IFG) and impaired glucose tolerance (IGT) detected by a standardized 75-gram …
Glycemic variability percentage: a novel method for assessing glycemic variability from continuous glucose monitor data
TA Peyser, AK Balo, BA Buckingham… - Diabetes technology …, 2018 - liebertpub.com
Background: High levels of glycemic variability are still observed in most patients with
diabetes with severe insulin deficiency. Glycemic variability may be an important risk factor …
diabetes with severe insulin deficiency. Glycemic variability may be an important risk factor …
Continuous glucose monitoring: current use in diabetes management and possible future applications
The recent announcement of the production of new low-cost continuous glucose monitoring
(CGM) sensors, the approval of marketed CGM sensors for making treatment decisions, and …
(CGM) sensors, the approval of marketed CGM sensors for making treatment decisions, and …
From stability to variability: classification of healthy individuals, prediabetes, and type 2 diabetes using glycemic variability indices from continuous glucose monitoring …
Objective: This study aims to investigate the continuum of glucose control from
normoglycemia to dysglycemia (HbA1c≥ 5.7%/39 mmol/mol) using metrics derived from …
normoglycemia to dysglycemia (HbA1c≥ 5.7%/39 mmol/mol) using metrics derived from …
Use of machine learning approaches in clinical epidemiological research of diabetes
Abstract Purpose of Review Machine learning approaches—which seek to predict outcomes
or classify patient features by recognizing patterns in large datasets—are increasingly …
or classify patient features by recognizing patterns in large datasets—are increasingly …
Assessment of glucose variability in subjects with prediabetes
N Chakarova, R Dimova, G Grozeva… - Diabetes research and …, 2019 - Elsevier
The aim of the study was to assess glucose variability in subjects with prediabetes by means
of CGM. Material and methods: 32 subjects with prediabetes–mean age 56.6±9.6 years …
of CGM. Material and methods: 32 subjects with prediabetes–mean age 56.6±9.6 years …
Dysglycemia in adults at risk for or living with non-insulin treated type 2 diabetes: Insights from continuous glucose monitoring
Background Continuous glucose monitoring (CGM) has demonstrable benefits for people
living with diabetes, but the supporting evidence is almost exclusively from White individuals …
living with diabetes, but the supporting evidence is almost exclusively from White individuals …
Pre-stroke glycemic variability estimated by glycated albumin is associated with early neurological deterioration and poor functional outcome in prediabetic patients …
SH Lee, Y Kim, SY Park, C Kim, YJ Kim… - Cerebrovascular …, 2021 - karger.com
Introduction: Whether glycemic variability prior to stroke increases the risk of stroke
outcomes in prediabetic patients presenting with acute ischemic stroke is still unclear. We …
outcomes in prediabetic patients presenting with acute ischemic stroke is still unclear. We …
Non-invasive wearables for remote monitoring of HbA1c and glucose variability: proof of concept
Introduction Diabetes prevalence continues to grow and there remains a significant
diagnostic gap in one-third of the US population that has pre-diabetes. Innovative, practical …
diagnostic gap in one-third of the US population that has pre-diabetes. Innovative, practical …